New metallothionein assay in Scrobicularia plana: heating effect and correlation with other biomarkers

Metallothionein (MT) and other biomarker levels were measured in Scrobicularia plana clams to assess pollution of the Guadalquivir Estuary possibly affected by metals released from Aznalcóllar pyrite mine in 1998. After optimizing reagent concentrations for monobromobimane derivatization, MT levels were quantified by reversed-phase high-performance liquid chromatography coupled to fluorescence detection (RP-HPLC-FD) in heated or unheated digestive gland extracts and compared to those obtained by differential pulse polarography (DPP). MT content assayed by RP-HPLC-FD in unheated samples was higher than that obtained by DPP and correlated better with metals and anti-oxidant activities. MT assay by RP-HPLC-FD in unheated extracts would be preferable for assessing metal pollution, due to its greater sensitivity and specificity. In addition to MT induction, glyoxalase II inhibition was well correlated with metal contents. Our results suggest that metals at the estuary do not originate from Aznalcóllar spill, but from those carried along by the river and deposited at its concave bank.     

Effects of repeated exposure to malathion on growth, food consumption, and locomotor performance of the western fence lizard (Sceloporus occidentalis)

Effects of repeated pollutant exposure on growth, locomotor performance, and behavior have rarely been evaluated in reptiles. We administered three doses of malathion (2.0, 20, or 100mg/kg body weight) to western fence lizards (Sceloporus occidentalis) over an 81day period. Eight and 23% mortality occurred at 20 and 100mg/kg (p=0.079) and 85% of lizards in the 100mg/kg group exhibited clinical symptoms of poisoning. Growth, food consumption, body condition index, and terrestrial locomotor performance were not significantly influenced by malathion. However, arboreal sprint velocity was significantly reduced in lizards receiving 100mg/kg. Fifty percent of lizards in the 100mg/kg group also refused to sprint in the arboreal setting (p=0.085). Based on these results, arboreal locomotor performance was the most sensitive metric of exposure we evaluated. Further study of compounds such as malathion is warranted due to highly variable application rates and exposure scenarios.     

On the search for mimetic patterns in environmental disclosure: an international perspective

In this paper, we assert and test the proposition that environmental disclosure (ED) is structured by institutionalised myths and that is why ED is decoupled from environmental performance and media pressures. Focusing on firms from Canada, France and Germany, findings show that ED mimetic isomorphism for different topics varies among countries and by industry sensitiveness to the environment. The results corroborate the institutional presumption that institutionalised myths vary among different contexts. Our findings also suggest that institutionalised ED structures may not reflect environmental performance, mimetic patterns being affected by environmental performance. However, the decoupling between ED mimetic isomorphism and environmental performance decrease when firms’ ED credibility is questioned by the media.     

Cracking the Achilles’ heel of energy performance contracting projects: the credit risk identification method for clients

ABSTRACT

A credit risk identification model is established to examine the credit status of Energy performance contracting (EPC) project clients (i.e., energy-using companies) in China based on rough set theory. The model is verified with data from 120 listed companies at different times. Study shows that lack of credit is one of the main obstacles to the implementation of EPC projects, and information asymmetry is the main reason for this lack of credit among potential clients in China. The credit risk identification method based on rough set theory can make up for the shortcomings of existing EPC projects in terms of credit risk identification, including redundant information and indicators, and unclear decision rules. Credit risk identification indicators of clients are dynamic. The research results can help energy service companies (ESCOs) determine the credit status of clients, facilitate cooperation between ESCOs and clients, and help explain the various dynamics of clients’ credit risk identification indicators over time.     

Investigation the effect of adding graphene oxide into diesel/higher alcohols blends on a diesel engine performance

ABSTRACT

This article aims to study the influence of the addition of graphene oxide nanoparticles (GO) to diesel/higher alcohols blends on the combustion, emission, and exergy parameters of a CI engine under various engine loads. The higher alcohols mainly n-butanol, n-heptanol, and n-octanol are blended with diesel at a volume fraction of 50%. Then, the 25 and 50 mg/L concentrations of GO are dispersed into diesel/higher alcohols blends using an ultrasonicator. The GO structures are examined using TEM, TGA, XRD and FTIR. The findings show that there is a reduction in p_max. and HRR when adding higher alcohols with diesel fuel. Regarding engine emission, there is a significant improvement in emissions formation with adding higher alcohols. The addition of GO into diesel/higher alcohols blends improves the brake thermal efficiency by 15%. Moreover, the p_max. and HRR are both enhanced by 4%. The CO, UHC and smoke formation are reduced considerably by 40%, 50 and 20%, respectively, while NO_x level is increased by 30% with adding GO. Finally, adding high percentages of n-butanol, n-heptanol, and n-octanol with diesel fuel with the presence of GO has the potential to achieve ultra-low CO, UHC, and smoke formation meanwhile keeping high thermal efficiency level.     

The impact of coal and non-coal consumption on China's energy performance improvement

China is the world's largest energy consumer, and coal accounts for a higher proportion of the country's total energy consumption, yet during its 12th five-year plan (2011–2015), the coal share among total energy consumption significantly decreased. Previous studies exploring energy performance typically used energy consumption as an input, but this lacks the analytical capacity for the structure of energy consumption. Thus, this study splits energy input into two different inputs, coal consumption and non-coal energy consumption, and based on their differences with other variables, uses the hybrid dynamic data envelopment analysis model to assess the energy performance of China's provincial industrial sector during the period 2011 to 2015. We then compare coal consumption's and non-coal consumption's rooms for improvement and conclude that provinces in eastern and central China should reduce the amount of coal consumption, thereby improving energy performance. Conversely, provinces in the western region should target a balance between energy utilization efficiency and coal consumption.     

连续流反应器中培养好氧颗粒污泥的运行效能研究

在连续流完全混合反应器(CSTR)中,采用不同进水方式,以乙酸钠作为碳源配制的人工配水作为原水,对好氧颗粒污泥的运行效能进行了试验研究。研究表明,采用不同进水方式运行的2个反应器在颗粒污泥出现后,运行效能差别不大;好氧颗粒污泥反应器运行高效稳定,在水力停留时间为1.5h、COD容积负荷为1.0kg/(m3·d)的条件下,对COD、TP、NH4+-N和TN的去除率分别为90%、85%、95%和60%,并具有明显的脱氮除磷效果;反应器中存在同步硝化反硝化现象。     

Safety climate factors, group differences and safety behaviour in road construction

This study determines the factor structure of safety climate within a road construction organization using a modified version of the safety climate questionnaire (SCQ). It also investigates the relationship between safety climate and safety performance. The SCQ was administered to 192 employees from two districts and in two job categories — construction and maintenance. A behavioural observation measure of safety performance was also developed. Factor analysis derived six factors, which were similar to those obtained in an earlier study using the SCQ. Differences in the safety climate of job sub-groups were found on two of the factors. No differences between the two districts were found. No relationship was found between safety climate and the safety performance measure. While identical safety climate factors cannot apply to all organizations, some general safety climate factors may emerge. Discussion focuses upon the measurement of safety climate.     

辉县市城区环境空气质量现状及污染防治对策

对辉县市城区2006—2011年间环境空气质量监测数据进行了评价,并对城区污染物浓度时空变化进行了分析。结果表明,辉县市城区大气污染主要表现为可吸入颗粒物污染严重,主要是能源结构不合理、锅炉废气污染严重、城区道路保洁方式落后等原因造成的,由此提出了合理规划城市布局、减少结构性污染等对策。     

Comparison of the Performance of Statistical Models in Forecasting Monthly Total Dissolved Solids in the Rio Grande1

Abudu, S., J.P. King, Z. Sheng, 2011. Comparison of the Performance of Statistical Models in Forecasting Monthly Total Dissolved Solids in the Rio Grande. Journal of the American Water Resources Association (JAWRA) 48(1): 10‐23. DOI: 10.1111/j.1752‐1688.2011.00587.x Abstract: This paper presents the application of autoregressive integrated moving average (ARIMA), transfer function‐noise (TFN), and artificial neural networks (ANNs) modeling approaches in forecasting monthly total dissolved solids (TDS) of water in the Rio Grande at El Paso, Texas. Predictability analysis was performed between the precipitation, temperature, streamflow rates at the site, releases from upstream reservoirs, and monthly TDS using cross‐correlation statistical tests. The chi‐square test results indicated that the average monthly temperature and precipitation did not show significant predictability on monthly TDS series. The performances of one‐ to three‐month‐ahead model forecasts for the testing period of 1984‐1994 showed that the TFN model that incorporated the streamflow rates at the site and Caballo Reservoir release improved monthly TDS forecasts slightly better than the ARIMA models. Except for one‐month‐ahead forecasts, the ANN models using the streamflow rates at the site as inputs resulted in no significant improvements over the TFN models at two‐month‐ahead and three‐month‐ahead forecasts. For three‐month‐ahead forecasts, the simple ARIMA showed similar performance compared to all other models. The results of this study suggested that simple deseasonalized ARIMA models could be used in one‐ to three‐month‐ahead TDS forecasting at the study site with a simple, explicit model structure and similar model performance as the TFN and ANN models for better water management in the Basin.